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Robotic mapping is a discipline related to computer vision [1] and cartography.The goal for an autonomous robot is to be able to construct (or use) a map (outdoor use) or floor plan (indoor use) and to localize itself and its recharging bases or beacons in it.
Consider a robot with an internal map of its environment. When the robot moves around, it needs to know where it is within this map. Determining its location and rotation (more generally, the pose) by using its sensor observations is known as robot localization. Because the robot may not always behave in a perfectly predictable way, it ...
Robot navigation means the robot's ability to determine its own position in its frame of reference and then to plan a path towards some goal location. In order to navigate in its environment, the robot or any other mobility device requires representation, i.e. a map of the environment and the ability to interpret that representation.
2005 DARPA Grand Challenge winner Stanley performed SLAM as part of its autonomous driving system. A map generated by a SLAM Robot. Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.
Occupancy Grid Mapping refers to a family of computer algorithms in probabilistic robotics for mobile robots which address the problem of generating maps from noisy and uncertain sensor measurement data, with the assumption that the robot pose is known. Occupancy grids were first proposed by H. Moravec and A. Elfes in 1985.
Map matching is the problem of how to match recorded geographic coordinates to a logical model of the real world, typically using some form of Geographic Information System. The most common approach is to take recorded, serial location points (e.g. from GPS ) and relate them to edges in an existing street graph (network), usually in a sorted ...
NASA WorldWind SDK Tutorial: This Tutorial was developed by the Institute for Geoinformatics from the University of Münster, Germany. It contains tutorials from setting up an Eclipse environment with the WorldWind API to building polygons from Linked Open Data geographic datasets. It contains important tips from beginners to advanced developers.
Karel is an educational programming language for beginners, created by Richard E. Pattis in his book Karel The Robot: A Gentle Introduction to the Art of Programming. Pattis used the language in his courses at Stanford University, California. The language is named after Karel Čapek, a Czech writer who introduced the word robot in his play R.U ...